cbc_interface.cc

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// Copyright 2010-2025 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
 
#include <cstdint>
#include <limits>
#include <memory>
#include <string>
#include <utility>
#include <vector>
 
#include "absl/base/attributes.h"
#include "absl/status/status.h"
#include "absl/strings/str_format.h"
#include "ortools/base/logging.h"
#include "ortools/base/timer.h"
#include "ortools/linear_solver/linear_solver.h"
 
#undef PACKAGE
#undef VERSION
#include "CbcConfig.h"
#include "CbcMessage.hpp"
#include "CbcModel.hpp"
#include "CoinModel.hpp"
#include "OsiClpSolverInterface.hpp"
 
// Heuristics
 
namespace operations_research {
 
class CBCInterface : public MPSolverInterface {
 public:
  // Constructor that takes a name for the underlying glpk solver.
  explicit CBCInterface(MPSolver* solver);
  ~CBCInterface() override;
 
  // ----- Reset -----
  void Reset() override;
 
  // Sets the optimization direction (min/max).
  void SetOptimizationDirection(bool maximize) override;
 
  // ----- Parameters -----
 
  absl::Status SetNumThreads(int num_threads) override {
    CHECK_GE(num_threads, 1);
    num_threads_ = num_threads;
    return absl::OkStatus();
  }
 
  // ----- Solve -----
  // Solve the problem using the parameter values specified.
  MPSolver::ResultStatus Solve(const MPSolverParameters& param) override;
 
  // TODO(user): separate the solve from the model extraction.
  virtual void ExtractModel() {}
 
  // Query problem type.
  bool IsContinuous() const override { return false; }
  bool IsLP() const override { return false; }
  bool IsMIP() const override { return true; }
 
  // Modify bounds.
  void SetVariableBounds(int var_index, double lb, double ub) override;
  void SetVariableInteger(int var_index, bool integer) override;
  void SetConstraintBounds(int row_index, double lb, double ub) override;
 
  // Add constraint incrementally.
  void AddRowConstraint(MPConstraint* ct) override;
  // Add variable incrementally.
  void AddVariable(MPVariable* var) override;
  // Change a coefficient in a constraint.
  void SetCoefficient(MPConstraint* const constraint,
                      const MPVariable* const variable, double new_value,
                      double old_value) override {
    sync_status_ = MUST_RELOAD;
  }
  // Clear a constraint from all its terms.
  void ClearConstraint(MPConstraint* const constraint) override {
    sync_status_ = MUST_RELOAD;
  }
 
  // Change a coefficient in the linear objective.
  void SetObjectiveCoefficient(const MPVariable* const variable,
                               double coefficient) override {
    sync_status_ = MUST_RELOAD;
  }
  // Change the constant term in the linear objective.
  void SetObjectiveOffset(double value) override { sync_status_ = MUST_RELOAD; }
  // Clear the objective from all its terms.
  void ClearObjective() override { sync_status_ = MUST_RELOAD; }
 
  // Number of simplex iterations
  int64_t iterations() const override;
  // Number of branch-and-bound nodes. Only available for discrete problems.
  int64_t nodes() const override;
 
  // Returns the basis status of a row.
  MPSolver::BasisStatus row_status(int constraint_index) const override {
    LOG(FATAL) << "Basis status only available for continuous problems";
    return MPSolver::FREE;
  }
  // Returns the basis status of a column.
  MPSolver::BasisStatus column_status(int variable_index) const override {
    LOG(FATAL) << "Basis status only available for continuous problems";
    return MPSolver::FREE;
  }
 
  void ExtractNewVariables() override {}
  void ExtractNewConstraints() override {}
  void ExtractObjective() override {}
 
  std::string SolverVersion() const override { return "Cbc " CBC_VERSION; }
 
  // TODO(user): Maybe we should expose the CbcModel build from osi_
  // instead, but a new CbcModel is built every time Solve is called,
  // so it is not possible right now.
  void* underlying_solver() override { return reinterpret_cast<void*>(&osi_); }
 
 private:
  // Reset best objective bound to +/- infinity depending on the
  // optimization direction.
  void ResetBestObjectiveBound();
 
  // Set all parameters in the underlying solver.
  void SetParameters(const MPSolverParameters& param) override;
  // Set each parameter in the underlying solver.
  void SetRelativeMipGap(double value) override;
  void SetPrimalTolerance(double value) override;
  void SetDualTolerance(double value) override;
  void SetPresolveMode(int value) override;
  void SetScalingMode(int value) override;
  void SetLpAlgorithm(int value) override;
 
  OsiClpSolverInterface osi_;
  // TODO(user): remove and query number of iterations directly from CbcModel
  int64_t iterations_;
  int64_t nodes_;
  // Special way to handle the relative MIP gap parameter.
  double relative_mip_gap_;
  int num_threads_ = 1;
};
 
// ----- Solver -----
 
// Creates a LP/MIP instance with the specified name and minimization objective.
CBCInterface::CBCInterface(MPSolver* const solver)
    : MPSolverInterface(solver),
      iterations_(0),
      nodes_(0),
      relative_mip_gap_(MPSolverParameters::kDefaultRelativeMipGap) {
  osi_.setStrParam(OsiProbName, solver_->name_);
  osi_.setObjSense(1);
}
 
CBCInterface::~CBCInterface() {}
 
// Reset the solver.
void CBCInterface::Reset() {
  osi_.reset();
  osi_.setObjSense(maximize_ ? -1 : 1);
  osi_.setStrParam(OsiProbName, solver_->name_);
  ResetExtractionInformation();
}
 
void CBCInterface::ResetBestObjectiveBound() {
  if (maximize_) {
    best_objective_bound_ = std::numeric_limits<double>::infinity();
  } else {
    best_objective_bound_ = -std::numeric_limits<double>::infinity();
  }
}
 
void CBCInterface::SetOptimizationDirection(bool maximize) {
  InvalidateSolutionSynchronization();
  if (sync_status_ == MODEL_SYNCHRONIZED) {
    osi_.setObjSense(maximize ? -1 : 1);
  } else {
    sync_status_ = MUST_RELOAD;
  }
}
 
namespace {
// CBC adds a "dummy" variable with index 0 to represent the objective offset.
int MPSolverVarIndexToCbcVarIndex(int var_index) { return var_index + 1; }
}  // namespace
 
void CBCInterface::SetVariableBounds(int var_index, double lb, double ub) {
  InvalidateSolutionSynchronization();
  if (sync_status_ == MODEL_SYNCHRONIZED) {
    osi_.setColBounds(MPSolverVarIndexToCbcVarIndex(var_index), lb, ub);
  } else {
    sync_status_ = MUST_RELOAD;
  }
}
 
void CBCInterface::SetVariableInteger(int var_index, bool integer) {
  InvalidateSolutionSynchronization();
  // TODO(user) : Check if this is actually a change.
  if (sync_status_ == MODEL_SYNCHRONIZED) {
    if (integer) {
      osi_.setInteger(MPSolverVarIndexToCbcVarIndex(var_index));
    } else {
      osi_.setContinuous(MPSolverVarIndexToCbcVarIndex(var_index));
    }
  } else {
    sync_status_ = MUST_RELOAD;
  }
}
 
void CBCInterface::SetConstraintBounds(int index, double lb, double ub) {
  InvalidateSolutionSynchronization();
  if (sync_status_ == MODEL_SYNCHRONIZED) {
    osi_.setRowBounds(index, lb, ub);
  } else {
    sync_status_ = MUST_RELOAD;
  }
}
 
void CBCInterface::AddRowConstraint(MPConstraint* const ct) {
  sync_status_ = MUST_RELOAD;
}
 
void CBCInterface::AddVariable(MPVariable* const var) {
  sync_status_ = MUST_RELOAD;
}
 
// Solve the LP/MIP. Returns true only if the optimal solution was revealed.
// Returns the status of the search.
MPSolver::ResultStatus CBCInterface::Solve(const MPSolverParameters& param) {
  // CBC requires unique variable and constraint names. By using Lookup*, we
  // generate variable and constraint indices and ensure the duplicate name
  // crash will happen here with a readable error message.
  if (!solver_->variables_.empty()) {
    solver_->LookupVariableOrNull(solver_->variables_[0]->name());
  }
  if (!solver_->constraints_.empty()) {
    solver_->LookupConstraintOrNull(solver_->constraints_[0]->name());
  }
 
  WallTimer timer;
  timer.Start();
 
  // Note that CBC does not provide any incrementality.
  if (param.GetIntegerParam(MPSolverParameters::INCREMENTALITY) ==
      MPSolverParameters::INCREMENTALITY_OFF) {
    Reset();
  }
 
  // Special case if the model is empty since CBC is not able to
  // handle this special case by itself.
  if (solver_->variables_.empty() && solver_->constraints_.empty()) {
    sync_status_ = SOLUTION_SYNCHRONIZED;
    result_status_ = MPSolver::OPTIMAL;
    objective_value_ = solver_->Objective().offset();
    best_objective_bound_ = solver_->Objective().offset();
    return result_status_;
  }
 
  // Finish preparing the problem.
  // Define variables.
  switch (sync_status_) {
    case MUST_RELOAD: {
      Reset();
      CoinModel build;
      // Create dummy variable for objective offset.
      build.addColumn(0, nullptr, nullptr, 1.0, 1.0,
                      solver_->Objective().offset(), "dummy", false);
      const int nb_vars = solver_->variables_.size();
      for (int i = 0; i < nb_vars; ++i) {
        MPVariable* const var = solver_->variables_[i];
        set_variable_as_extracted(i, true);
        const double obj_coeff = solver_->Objective().GetCoefficient(var);
        if (var->name().empty()) {
          build.addColumn(0, nullptr, nullptr, var->lb(), var->ub(), obj_coeff,
                          nullptr, var->integer());
        } else {
          build.addColumn(0, nullptr, nullptr, var->lb(), var->ub(), obj_coeff,
                          var->name().c_str(), var->integer());
        }
      }
 
      // Define constraints.
      int max_row_length = 0;
      for (int i = 0; i < solver_->constraints_.size(); ++i) {
        MPConstraint* const ct = solver_->constraints_[i];
        set_constraint_as_extracted(i, true);
        if (ct->coefficients_.size() > max_row_length) {
          max_row_length = ct->coefficients_.size();
        }
      }
      std::unique_ptr<int[]> indices(new int[max_row_length]);
      std::unique_ptr<double[]> coefs(new double[max_row_length]);
 
      for (int i = 0; i < solver_->constraints_.size(); ++i) {
        MPConstraint* const ct = solver_->constraints_[i];
        const int size = ct->coefficients_.size();
        int j = 0;
        for (const auto& entry : ct->coefficients_) {
          const int index = MPSolverVarIndexToCbcVarIndex(entry.first->index());
          indices[j] = index;
          coefs[j] = entry.second;
          j++;
        }
        if (ct->name().empty()) {
          build.addRow(size, indices.get(), coefs.get(), ct->lb(), ct->ub());
        } else {
          build.addRow(size, indices.get(), coefs.get(), ct->lb(), ct->ub(),
                       ct->name().c_str());
        }
      }
      osi_.loadFromCoinModel(build);
      break;
    }
    case MODEL_SYNCHRONIZED: {
      break;
    }
    case SOLUTION_SYNCHRONIZED: {
      break;
    }
  }
 
  // Changing optimization direction through OSI so that the model file
  // (written through OSI) has the correct optimization duration.
  osi_.setObjSense(maximize_ ? -1 : 1);
 
  sync_status_ = MODEL_SYNCHRONIZED;
  VLOG(1) << absl::StrFormat("Model built in %.3f seconds.", timer.Get());
 
  ResetBestObjectiveBound();
 
  // Solve
  CbcModel model(osi_);
 
  // Set log level.
  CoinMessageHandler message_handler;
  model.passInMessageHandler(&message_handler);
  if (quiet_) {
    message_handler.setLogLevel(0, 0);  // Coin messages
    message_handler.setLogLevel(1, 0);  // Clp messages
    message_handler.setLogLevel(2, 0);  // Presolve messages
    message_handler.setLogLevel(3, 0);  // Cgl messages
  } else {
    message_handler.setLogLevel(0, 1);  // Coin messages
    message_handler.setLogLevel(1, 1);  // Clp messages
    message_handler.setLogLevel(2, 1);  // Presolve messages
    message_handler.setLogLevel(3, 1);  // Cgl messages
  }
 
  // Time limit.
  if (solver_->time_limit() != 0) {
    VLOG(1) << "Setting time limit = " << solver_->time_limit() << " ms.";
    model.setMaximumSeconds(solver_->time_limit_in_secs());
  }
 
  // And solve.
  timer.Restart();
 
  // Here we use the default function from the command-line CBC solver.
  // This enables to activate all the features and get the same performance
  // as the CBC stand-alone executable. The syntax is ugly, however.
  SetParameters(param);
  // Always turn presolve on (it's the CBC default and it consistently
  // improves performance).
  model.setTypePresolve(0);
  // Special way to set the relative MIP gap parameter as it cannot be set
  // through callCbc.
  model.setAllowableFractionGap(relative_mip_gap_);
  // NOTE: Trailing space is required to avoid buffer overflow in cbc.
  int return_status =
      num_threads_ == 1
          ? callCbc("-solve ", model)
          : callCbc(absl::StrCat("-threads ", num_threads_, " -solve "), model);
  const int kBadReturnStatus = 777;
  CHECK_NE(kBadReturnStatus, return_status);  // Should never happen according
                                              // to the CBC source
 
  VLOG(1) << absl::StrFormat("Solved in %.3f seconds.", timer.Get());
 
  // Check the status: optimal, infeasible, etc.
  int tmp_status = model.status();
 
  VLOG(1) << "cbc result status: " << tmp_status;
  /* Final status of problem
     (info from third_party/cbc/.../CbcSolver.cpp,
      See http://cs?q="cbc+status"+file:CbcSolver.cpp)
     Some of these can be found out by is...... functions
     -1 before branchAndBound
     0 finished - check isProvenOptimal or isProvenInfeasible to see
     if solution found
     (or check value of best solution)
     1 stopped - on maxnodes, maxsols, maxtime
     2 difficulties so run was abandoned
     (5 event user programmed event occurred)
  */
  switch (tmp_status) {
    case 0:
      // Order of tests counts; if model.isContinuousUnbounded() returns true,
      // then so does model.isProvenInfeasible()!
      if (model.isProvenOptimal()) {
        result_status_ = MPSolver::OPTIMAL;
      } else if (model.isContinuousUnbounded()) {
        result_status_ = MPSolver::UNBOUNDED;
      } else if (model.isProvenInfeasible()) {
        result_status_ = MPSolver::INFEASIBLE;
      } else if (model.isAbandoned()) {
        result_status_ = MPSolver::ABNORMAL;
      } else {
        result_status_ = MPSolver::ABNORMAL;
      }
      break;
    case 1:
      if (model.bestSolution() != nullptr) {
        result_status_ = MPSolver::FEASIBLE;
      } else {
        result_status_ = MPSolver::NOT_SOLVED;
      }
      break;
    default:
      result_status_ = MPSolver::ABNORMAL;
      break;
  }
 
  if (result_status_ == MPSolver::OPTIMAL ||
      result_status_ == MPSolver::FEASIBLE) {
    // Get the results
    objective_value_ = model.getObjValue();
    VLOG(1) << "objective=" << objective_value_;
    const double* const values = model.bestSolution();
    if (values != nullptr) {
      // if optimal or feasible solution is found.
      for (int i = 0; i < solver_->variables_.size(); ++i) {
        MPVariable* const var = solver_->variables_[i];
        const int var_index = MPSolverVarIndexToCbcVarIndex(var->index());
        const double val = values[var_index];
        var->set_solution_value(val);
        VLOG(3) << var->name() << "=" << val;
      }
    } else {
      VLOG(1) << "No feasible solution found.";
    }
  }
 
  iterations_ = model.getIterationCount();
  nodes_ = model.getNodeCount();
  best_objective_bound_ = model.getBestPossibleObjValue();
  VLOG(1) << "best objective bound=" << best_objective_bound_;
 
  sync_status_ = SOLUTION_SYNCHRONIZED;
 
  return result_status_;
}
 
// ------ Query statistics on the solution and the solve ------
 
int64_t CBCInterface::iterations() const {
  if (!CheckSolutionIsSynchronized()) return kUnknownNumberOfNodes;
  return iterations_;
}
 
int64_t CBCInterface::nodes() const {
  if (!CheckSolutionIsSynchronized()) return kUnknownNumberOfIterations;
  return nodes_;
}
 
// ----- Parameters -----
 
// The support for parameters in CBC is intentionally sparse. There is
// a memory leak in callCbc that prevents to pass parameters through
// it, so handling parameters would require a comprehensive rewrite
// of the code. I will improve the parameter support only if there is
// a relevant use case.
 
void CBCInterface::SetParameters(const MPSolverParameters& param) {
  SetCommonParameters(param);
  SetMIPParameters(param);
}
 
void CBCInterface::SetRelativeMipGap(double value) {
  relative_mip_gap_ = value;
}
 
void CBCInterface::SetPrimalTolerance(double value) {
  // Skip the warning for the default value as it coincides with
  // the default value in CBC.
  if (value != MPSolverParameters::kDefaultPrimalTolerance) {
    SetUnsupportedDoubleParam(MPSolverParameters::PRIMAL_TOLERANCE);
  }
}
 
void CBCInterface::SetDualTolerance(double value) {
  // Skip the warning for the default value as it coincides with
  // the default value in CBC.
  if (value != MPSolverParameters::kDefaultDualTolerance) {
    SetUnsupportedDoubleParam(MPSolverParameters::DUAL_TOLERANCE);
  }
}
 
void CBCInterface::SetPresolveMode(int value) {
  switch (value) {
    case MPSolverParameters::PRESOLVE_ON: {
      // CBC presolve is always on.
      break;
    }
    default: {
      SetUnsupportedIntegerParam(MPSolverParameters::PRESOLVE);
    }
  }
}
 
void CBCInterface::SetScalingMode(int value) {
  SetUnsupportedIntegerParam(MPSolverParameters::SCALING);
}
 
void CBCInterface::SetLpAlgorithm(int value) {
  SetUnsupportedIntegerParam(MPSolverParameters::LP_ALGORITHM);
}
 
namespace {
 
// See MpSolverInterfaceFactoryRepository for details.
const void* const kRegisterCBC ABSL_ATTRIBUTE_UNUSED = [] {
  MPSolverInterfaceFactoryRepository::GetInstance()->Register(
      [](MPSolver* const solver) { return new CBCInterface(solver); },
      MPSolver::CBC_MIXED_INTEGER_PROGRAMMING);
  return nullptr;
}();
 
}  // namespace
 
}  // namespace operations_research